{"id":"https://openalex.org/W4414085626","doi":"https://doi.org/10.1109/tnnls.2025.3601130","title":"Robust Missing Value Imputation With Proximal Optimal Transport for Low-Quality IIoT Data","display_name":"Robust Missing Value Imputation With Proximal Optimal Transport for Low-Quality IIoT Data","publication_year":2025,"publication_date":"2025-09-09","ids":{"openalex":"https://openalex.org/W4414085626","doi":"https://doi.org/10.1109/tnnls.2025.3601130","pmid":"https://pubmed.ncbi.nlm.nih.gov/40924520"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3601130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3601130","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104104327","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-3243-487X"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Wang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100619470","display_name":"Zhichao Chen","orcid":"https://orcid.org/0000-0001-5785-0741"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhichao Chen","raw_affiliation_strings":["College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085228064","display_name":"Yuan Shen","orcid":"https://orcid.org/0000-0001-5655-6962"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Shen","raw_affiliation_strings":["College of Control Science and Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Control Science and Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100946139","display_name":"Hui Zheng","orcid":"https://orcid.org/0000-0001-7170-5700"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Zheng","raw_affiliation_strings":["Microsoft Inc.,, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Inc.,, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103665818","display_name":"Yang De-gui","orcid":"https://orcid.org/0000-0003-1604-9792"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degui Yang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069781785","display_name":"Dangjun Zhao","orcid":"https://orcid.org/0000-0001-9286-1999"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dangjun Zhao","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5119577405","display_name":"Buge Liang","orcid":"https://orcid.org/0000-0002-5344-2799"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Buge Liang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5104104327"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":null,"apc_paid":null,"fwci":2.4849,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91392467,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"37","issue":"1","first_page":"82","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.9045000076293945},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6759999990463257},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6266999840736389},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.36000001430511475},{"id":"https://openalex.org/keywords/simplex","display_name":"Simplex","score":0.35600000619888306},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.32749998569488525}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.9045000076293945},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6759999990463257},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6431999802589417},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6266999840736389},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4909000098705292},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C62438384","wikidata":"https://www.wikidata.org/wiki/Q331350","display_name":"Simplex","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33320000767707825},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3093000054359436},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3005000054836273},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2621000111103058}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3601130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3601130","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:40924520","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40924520","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1781481323","https://openalex.org/W1970394074","https://openalex.org/W2064186732","https://openalex.org/W2540224322","https://openalex.org/W2788805965","https://openalex.org/W2902048196","https://openalex.org/W2996397717","https://openalex.org/W3009330671","https://openalex.org/W3034337242","https://openalex.org/W3044668092","https://openalex.org/W3098198535","https://openalex.org/W3175212568","https://openalex.org/W3177242545","https://openalex.org/W3211445244","https://openalex.org/W4206471589","https://openalex.org/W4206713150","https://openalex.org/W4250589301","https://openalex.org/W4281766517","https://openalex.org/W4283079434","https://openalex.org/W4313524849","https://openalex.org/W4381785896","https://openalex.org/W4387092352","https://openalex.org/W4387966578","https://openalex.org/W4389339573","https://openalex.org/W4391216848","https://openalex.org/W4391468387","https://openalex.org/W4393148126","https://openalex.org/W4401536775","https://openalex.org/W4401863578","https://openalex.org/W4402508047","https://openalex.org/W4404520619","https://openalex.org/W4404609273","https://openalex.org/W4405022222","https://openalex.org/W4405306095","https://openalex.org/W4406495710","https://openalex.org/W4408399367","https://openalex.org/W4411346340","https://openalex.org/W4412877125","https://openalex.org/W4413212276","https://openalex.org/W4414359275","https://openalex.org/W4415795730"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W2903115227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"Accurate":[0],"imputation":[1,24,46,124,130,150],"of":[2,37,55,93,114,146],"missing":[3,128],"data":[4,45,129],"is":[5,77,108,119],"crucial":[6],"in":[7],"the":[8,53,67,74,80,102,106,111,123,144],"Industrial":[9],"Internet-of-Things":[10],"(IIoT),":[11],"where":[12,73,105],"operations":[13],"are":[14],"often":[15],"compromised":[16],"by":[17,79],"noisy":[18,61,97,136],"samples":[19],"from":[20],"harsh":[21],"environments.":[22],"Traditional":[23],"methods":[25],"struggle":[26],"with":[27,84,96],"such":[28],"noise":[29],"due":[30],"to":[31,59,109,121,135],"their":[32],"black-box":[33],"nature":[34],"or":[35],"lack":[36],"adaptability.":[38],"To":[39],"address":[40],"this":[41],"issue,":[42],"we":[43,64,100],"recast":[44],"as":[47],"a":[48,85],"distribution":[49],"alignment":[50],"challenge,":[51],"utilizing":[52],"flexibility":[54],"optimal":[56],"transport":[57,112],"(OT)":[58],"handle":[60],"samples.":[62,98,137],"Specifically,":[63],"first":[65],"introduce":[66],"Proximal":[68],"Optimal":[69],"Transport":[70],"(POT)":[71],"problem,":[72],"transportation":[75],"cost":[76,113],"obtained":[78],"network":[81],"simplex":[82],"approach":[83],"selective":[86],"matching":[87,94],"mechanism,":[88],"which":[89,126],"renders":[90],"it":[91],"capable":[92],"distributions":[95],"Subsequently,":[99],"propose":[101],"POT-I":[103,147],"framework,":[104],"objective":[107],"minimize":[110],"POT.":[115],"The":[116],"produced":[117],"gradient":[118],"used":[120],"refine":[122],"value,":[125],"achieves":[127],"(MDI)":[131],"while":[132],"getting":[133],"robustness":[134],"Experiments":[138],"on":[139],"real-world":[140],"IIoT":[141],"datasets":[142],"demonstrate":[143],"superiority":[145],"over":[148],"state-of-the-art":[149],"methods.":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}